{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T11:02:32Z","timestamp":1783162952388,"version":"3.54.6"},"reference-count":18,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2023,8,16]],"date-time":"2023-08-16T00:00:00Z","timestamp":1692144000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Veterinary Medicines Directorate","award":["PO20000331"],"award-info":[{"award-number":["PO20000331"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,10,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Accurate surveillance of livestock antibiotic usage (ABU) at the farm level is an increasingly important part of national antibiotic stewardship initiatives. Numerous ABU indicators or metrics have been developed in Europe and North America but the comparability of these metrics is poorly understood. For policymakers, understanding the relationship between metrics is important when considering the risks posed by ABU and how to regulate them, at the national level, and regulate international trade access in livestock products between countries who use different ABU metrics.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Objectives<\/jats:title>\n                  <jats:p>To quantify the patterns of ABU among beef (cattle) and lamb (sheep) production systems. To explore ABU variation between farm types across seven ABU metrics developed in Europe and North America using a common dataset of sheep and beef farms\u2019 antibiotic purchases from the UK.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>A dataset of &amp;gt;16\u200a200 antibiotic sales events to 686 farm enterprises of different types underwent quantitative analysis. Correlation matrixes were generated for seven international ABU metrics.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>ABU was significantly higher among calf-rearers. Across all farm types, tetracyclines and \u03b2-lactams were the predominant groups by mass, but represent a similar dose equivalent to macrolides across most farm types. Good agreement (&amp;gt;0.9) was observed between metrics.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Reliable metrics to accurately benchmark farms are crucial for maintaining confidence of farmers in the fairness of any surveillance system, especially when the ranking of any given system may be linked to financial subsidies or penalties and also when negotiating import and export access for livestock products between countries.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jac\/dkad259","type":"journal-article","created":{"date-parts":[[2023,8,16]],"date-time":"2023-08-16T08:18:56Z","timestamp":1692173936000},"page":"2496-2504","source":"Crossref","is-referenced-by-count":3,"title":["Comparison of multiple international metrics for benchmarking antibiotic usage (ABU) using UK beef and sheep data"],"prefix":"10.1093","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6085-9763","authenticated-orcid":false,"given":"Peers","family":"Davies","sequence":"first","affiliation":[{"name":"Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool , Leahurst Campus, Wirral , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Hyde","sequence":"additional","affiliation":[{"name":"School of Veterinary Medicine and Science, University of Nottingham , Sutton Bonington Campus, Leicestershire , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7902-0914","authenticated-orcid":false,"given":"Alexander","family":"Corbishley","sequence":"additional","affiliation":[{"name":"Royal (Dick) School of Veterinary Studies and The Roslin Institute, University of Edinburgh , Easter Bush Campus, Midlothian , UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,8,16]]},"reference":[{"key":"2023100302095542800_dkad259-B1","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1093\/jac\/dkt443","article-title":"Correlation between veterinary antimicrobial use and antimicrobial resistance in food-producing animals: a report on seven countries","volume":"69","author":"Chantziaras","year":"2014","journal-title":"J Antimicrob Chemother"},{"key":"2023100302095542800_dkad259-B2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1017\/S0950268815000722","article-title":"Scoping review to identify potential non-antimicrobial interventions to mitigate antimicrobial resistance in commensal enteric bacteria in North American cattle production systems","volume":"144","author":"Murphy","year":"2016","journal-title":"Epidemiol Infect"},{"key":"2023100302095542800_dkad259-B3","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1186\/s40168-017-0378-z","article-title":"The rumen microbiome as a reservoir of antimicrobial resistance and pathogenicity genes is directly affected by diet in beef cattle","volume":"5","author":"Auffret","year":"2017","journal-title":"Microbiome"},{"key":"2023100302095542800_dkad259-B4","author":"DEFRA."},{"key":"2023100302095542800_dkad259-B5","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1136\/vr.104501","article-title":"Quantitative analysis of antibiotic usage in British sheep flocks","volume":"181","author":"Davies","year":"2017","journal-title":"Vet Rec"},{"key":"2023100302095542800_dkad259-B6","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1136\/vr.104614","article-title":"Quantitative analysis of antimicrobial use on British dairy farms","volume":"181","author":"Hyde","year":"2017","journal-title":"Vet 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use affect farm ranking?","volume":"7","author":"O\u2019Neill","year":"2020","journal-title":"Front Vet Sci"},{"key":"2023100302095542800_dkad259-B12","doi-asserted-by":"crossref","first-page":"330","DOI":"10.3389\/fvets.2019.00330","article-title":"Calculation of antimicrobial use indicators in beef feedlots\u2014effects of choice of metric and standardized values","volume":"6","author":"Brault","year":"2019","journal-title":"Front Vet Sci"},{"key":"2023100302095542800_dkad259-B13","author":"DANMAP","year":"2019"},{"key":"2023100302095542800_dkad259-B14","author":"CIPARS."},{"key":"2023100302095542800_dkad259-B15","author":"SDa","year":"2019"},{"key":"2023100302095542800_dkad259-B16","author":"Robinson"},{"key":"2023100302095542800_dkad259-B17","author":"R Team"},{"key":"2023100302095542800_dkad259-B18","author":"Breiman","year":"2022"}],"container-title":["Journal of Antimicrobial 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